In the Music Mission, we build the tools and services that enable creators to express themselves, promote their work, and connect with fans. Discovery Mode is a key promotional tool that helps artists, labels, and licensors grow their audience while maintaining a high-quality listener experience.We are looking for a Backend focused engineer to join the OASIS team. OASIS builds and operates the systems that power promotion delivery and optimization within Discovery Mode. Our work ensures that promotional content isn’t just 'surfaced', but is intelligently allocated by balancing complex, competing objectives across our entire ecosystem.The team is distributed and highly collaborative, working closely with Personalization (PZN) to serve high-quality promotion signals. You’ll be part of a small, impactful group of engineers across data and machine learning, owning a core piece of infrastructure that enables promotion delivery at scale.What You'll DoOwn and evolve backend systems that deliver promotion scores to personalization systems (PZN)Build and maintain services that support promotion allocation and delivery at scaleCollaborate closely with machine learning engineers and data engineers to improve signal quality and system performanceContribute to system design decisions that impact a critical part of Spotify’s discovery ecosystemImprove reliability, scalability, and observability of existing infrastructurePartner with cross-functional teams to ensure seamless integration with personalization workflowsGradually expand your scope into adjacent areas such as data pipelines or ML-adjacent systemsWho You AreYou have experience building backend systems using Java or similar languagesYou are comfortable working across systems and are interested in learning beyond pure backend (e.g., data or ML systems)You are driven to leverage AI to improve our systems, and eager to find practical ways to apply itYou have experience working with or exposure to Scala, Python, or data/ML workflowsYou are excited to grow into a T-shaped engineer with breadth across backend, data, and ML-adjacent domainsYou care about ownership and are motivated to take responsibility for evolving critical systemsYou collaborate effectively with cross-functional teams, including personalization and data partnersWhere You'll BeWe offer you the flexibility to work where you work best! For this role, you can be within the North America region as long as we have a work location.This team operates within the Eastern Standard time zone for collaboration.The United States base range for this position is $132,949- $189,927 equity. The benefits available for this position include health insurance, six month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, 13 paid flexible holidays, paid sick leave. These ranges may be modified in the future.Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens.At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we’re here to support you in any way we can.Spotify transformed music listening forever when we launched in 2008. Our mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators. Everything we do is driven by our love for music and podcasting. Today, we are the world’s most popular audio streaming subscription service.